1. Background Field
Embodiments of the subject matter described herein are related generally to determining a position estimate for a mobile device, and more particularly to using information from two different sets of sensors to determine the position estimate.
2. Relevant Background
Most smartphone devices contain both motion sensors and light sensors that can be used to infer the position of a device with respect to the user, e.g. device is in the users hand, pants pocket, shirt pocket, backpack, purse, resting on a desk, etc. . . . . Motion sensors, such as accelerometers, magnetometers, and gyroscopes, are capable of recording the movements and orientation of the device. Sensors such as the ambient light sensor, the proximity sensor, and the camera, report on the environment surrounding the device. In particular, the ambient light sensor (ALS) reports the intensity of the light (e.g., in lux) impinging on the front face of the device while the proximity sensor reports the intensity of emitted infra-red light reflecting off objects that are proximate to the front of the device. The camera is capable of recording a detailed image containing millions of colored pixels, but can also be used as a back-side light sensor, capturing only the average intensities of red, green and blue light impinging on the back face of the device.
Unfortunately, light sensors, such as ALS, proximity sensor, and camera on typical mobile devices have drawbacks. The ALS output is often heavily quantized in low-layer software such that the available output at high-layers takes on one of only a handful of intensity values (for example, it takes on only one of four values, 10, 325, 7650 and 21525 lux in some current smartphones). The proximity sensor output at high-layers is typically 0 or 1, crudely representing whether an object is proximate to the front-face of the device, or not. The camera intensity is typically subject to automatic gain control (AGC) at low-layer software, which makes it difficult to directly map the output to a lux value.
Both motion and light sensors are each capable of providing information on the position of the device relative to the user. Combining the information, however, is problematic, as the resulting position estimates will sometimes disagree. Additionally, position estimates from light sensors may be unreliable, as they can be heavily quantized and are inherently tied to the amount of light in the ambient environment. For example, a current mobile device may output an ALS reading of 10 lux when the true light intensity is anywhere between 0 and 167.5 lux. Thus, it may be difficult to distinguish between when a front face is occluded vs. when the device is in a moderate lit family room. Another example of unreliability is the proximity sensor, which in many devices reports a positive reading when inside the pant pocket of light colored denim jeans, but a negative reading when inside the pant pocket of dark colored denim jeans.